Learning, Signaling, and Social Preferences in Public-Good Games

Abstract

This study compares the empirical performance of a variety of learning models and theories of social preferences in the context of experimental games involving the provision of public goods. Parameters are estimated via maximum likelihood estimation. We also performed estimations to identify different types of agents and distributions of parameters. The estimated models suggest that the players of such games take into account the learning of others and are belief learners. Despite these interesting findings, we conclude that a powerful method of model selection of agent-based models on dynamic social dilemma experiments is still lacking.